Adaptive control for immersive experience delivery

ABSTRACT

A combined video of a scene may be generated for applications such as virtual reality or augmented reality. In one method, a data store may store video data with a first portion having a first importance metric, and a second portion having a second importance metric, denoting that viewing of the first portion is more likely and/or preferential to viewing of the second portion. The subset may be retrieved and used to generate viewpoint video from a virtual viewpoint corresponding to a viewer&#39;s viewpoint. The viewpoint video may be displayed on a display device. One of storing the video data, retrieving the subset, and using the subset to generate the viewpoint video may include, based on the difference between the first and second importance metrics, expediting and/or enhancing performance of the step for the first portion, relative to the second portion.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is related to U.S. application Ser. No.15/590,841 for “Vantage Generation and Interactive Playback,” filed onMay 9, 2017, the disclosure of which is incorporated herein byreference.

The present application is also related to U.S. application Ser. No.15/590,877 for “Spatial Random Access Enabled Video System with aThree-Dimensional Viewing Volume,” filed on May 9, 2017, the disclosureof which is incorporated herein by reference.

The present application is also related to U.S. application Ser. No.15/590,951 for “Wedge-Based Light-Field Video Capture,” filed on May 9,2017, the disclosure of which is incorporated herein by reference.

TECHNICAL FIELD

The present document relates to the use of importance metrics tostreamline the capture, storage, delivery, and/or rendering of videodata for an immersive experience such as virtual reality or augmentedreality.

BACKGROUND

As better and more immersive display devices are created for providingvirtual reality (VR) and augmented reality (AR) environments, it isdesirable to be able to capture high quality imagery and video for thesesystems. In a stereo VR environment, a user sees separate views for eacheye; also, the user may turn and move his or her head while viewing. Asa result, it is desirable that the user receive high-resolution stereoimagery that is consistent and correct for any viewing position andorientation in the volume within which a user may move his or her head.

The most immersive virtual reality and augmented reality experienceshave six degrees of freedom, parallax, and view-dependent lighting. Theresulting video data can be quite voluminous, requiring significantresources in terms of storage, delivery bandwidth, and/or processingpower. These resources are often constrained, for example, by theprocessing power of the user's computer, the storage capacity of theuser's computer, the bandwidth of the user's connection to a datasource, and/or other factors. Such factors significantly limit thequality of the viewer's experience.

SUMMARY

Various embodiments of the described system and method utilizeimportance metrics to indicate the relative likelihood and/ordesirability of viewing different portions of video data. For example, afirst portion of the video data for a virtual reality or augmentedreality experience may have a first importance metric, and a secondportion of the video data may have a second importance metric. Adifference between the first and second importance metrics may denotethat the first portion is more likely to be viewed and/or preferred forviewing, relative to the second portion.

A subset of the video data may be retrieved and used to generateviewpoint video from a virtual viewpoint corresponding to a viewer'sactual viewpoint. Storage, retrieval, and/or generation of the viewpointvideo may be carried out with respect to the importance metrics, suchthat one or more of these tasks are expedited and/or enhanced for thefirst portion, relative to the second portion.

In some embodiments, the video data may be divided into a plurality ofvantage video data sets, each of which represents a view from one of aplurality of vantages within a viewing volume containing the virtualviewpoint. The position of the viewer's viewpoint may be used todetermine which vantage video data sets will be used to generate theviewpoint video. The first and second portions of the video data mayeach include one or more of the vantages, such that some vantages areexpedited and/or enhanced for storage, retrieval, and/or processing,relative to other vantages.

Additionally or alternatively, the first portion of the video data maybe for a first region of the viewing volume, and the second portion ofthe video data may be for a second region of the viewing volume. Variousparameters such as a number of vantages, a density of vantages,locations of vantages, a number of vantages used to generate theviewpoint video, lighting applied to vantages, and resolution ofvantages may be enhanced for the first region, relative to the secondvolume.

Further, each vantage may be divided into a plurality of tiles, each ofwhich represents the view from the vantage along a viewing direction.The orientation of the viewer's viewpoint may be used to determine whichtiles will be used to generate the viewpoint video. The first and secondportions of the video data may each include one or more of the tiles foreach of a plurality of the vantages, such that some tiles are expeditedand/or enhanced for storage, retrieval, and/or processing, relative toother tiles.

Additionally or alternatively, the first portion of the video data maybe for a first set of tiles oriented along a first set of viewingdirections, and the second portion of the video data may be for a secondset of tiles oriented along a second set of viewing directions. Variousparameters such as tile spatial resolution, tile temporal resolution,tile color depth, and tile bit rate may be enhanced for the first set oftiles, relative to the second set of tiles.

The importance metrics may be established in a wide variety of ways. Forexample, the importance metric may be based on viewing data indicatingwhich portions of the experience have been viewed or preferred by moreviewers, user input from an author of the experience indicating whichportions are more likely or desirable for viewing and/or which portionscorrespond to other stimuli presented as part of the experience, and/oranalysis of the video data and/or accompanying audio data thatdetermines which portions are more likely or desirable for viewing.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate several embodiments. Together withthe description, they serve to explain the principles of theembodiments. One skilled in the art will recognize that the particularembodiments illustrated in the drawings are merely exemplary, and arenot intended to limit scope.

FIG. 1 is a flow diagram depicting a method for delivering video for avirtual reality or augmented reality experience, according to oneembodiment.

FIG. 2 is a screenshot diagram depicting a frame from a viewpoint videoof a virtual reality experience, according to one embodiment.

FIG. 3 is a screenshot diagram depicting the screenshot diagram of FIG.2, overlaid with a viewing volume for each of the eyes, according to oneembodiment.

FIG. 4 is a screenshot diagram depicting the view after the headset hasbeen moved forward, toward the scene of FIG. 2, according to oneembodiment.

FIG. 5 is a screenshot diagram depicting the color channel from a singlevantage, such as one of the vantages of FIG. 3, according to oneembodiment.

FIG. 6 is a diagram depicting the manner in which the tiles of avantage, such as one of the vantages of FIG. 3, may be selected,according to one embodiment.

FIG. 7 is a screenshot diagram depicting the depth channel from thevantage used to provide the screenshot diagram of FIG. 5, according toone embodiment.

FIG. 8 is a diagram depicting a portion of a scene in which two objectsare positioned such that an occluded area exists behind the objects,according to one embodiment.

FIG. 9 is a diagram depicting the portion of the scene of FIG. 9, inwhich another vantage has been added to enhance viewing of the occludedarea, according to one embodiment.

FIG. 10 is a screenshot diagram depicting the vantages traversed by asingle viewer and accumulated over time, according to one embodiment.

FIG. 11 is a screenshot diagram depicting the vantages traversed bymultiple viewers and accumulated over time, according to one embodiment.

FIG. 12 is a diagram depicting a vantage, according to one embodiment.

DETAILED DESCRIPTION

Multiple methods for capturing image and/or video data in a light-fieldvolume and creating virtual views from such data are described. Thedescribed embodiments may provide for capturing continuous or nearlycontinuous light-field data from many or all directions facing away fromthe capture system, which may enable the generation of virtual viewsthat are more accurate and/or allow viewers greater viewing freedom.

Definitions

For purposes of the description provided herein, the followingdefinitions are used:

-   -   Augmented reality: an immersive viewing experience in which        images presented to the viewer are based on the location and/or        orientation of the viewer's head and/or eyes, and are presented        in conjunction with the viewer's view of actual objects in the        viewer's environment.    -   Conventional image: an image in which the pixel values are not,        collectively or individually, indicative of the angle of        incidence at which light is received on the surface of the        sensor.    -   Depth: a representation of distance between an object and/or        corresponding image sample and the entrance pupil of the optics        of the capture system.    -   Image: a two-dimensional array of pixel values, or pixels, each        specifying a color.    -   Importance metric: an indicator of the importance of a subset of        video data.    -   Input device: any device that receives input from a user.    -   Light-field camera: any camera capable of capturing light-field        images.    -   Light-field data: data indicative of the angle of incidence at        which light is received on the surface of the sensor.    -   Light-field image: an image that contains a representation of        light-field data captured at the sensor, which may be a        four-dimensional sample representing information carried by ray        bundles received by a single light-field camera.    -   Light-field volume: the combination of all light-field images        that represents, either fully or sparsely, light rays entering        the physical space defined by the light-field volume.    -   Processor: any processing device capable of processing digital        data, which may be a microprocessor, ASIC, FPGA, or other type        of processing device.    -   Ray bundle, “ray,” or “bundle”: a set of light rays recorded in        aggregate by a single pixel in a photosensor.    -   Scene: an arrangement of objects and/or people to be filmed.    -   Sensor, “photosensor,” or “image sensor”: a light detector in a        camera capable of generating images based on light received by        the sensor.    -   Stereo virtual reality: an extended form of virtual reality in        which each eye is shown a different view of the virtual world,        enabling stereoscopic three-dimensional perception.    -   Tile: a portion of a vantage video data set corresponding to a        particular viewing direction.    -   Vantage: a position in three-dimensional space with associated        video data.    -   Vantage video data set: the portion of video data associated        with a particular vantage.    -   Video data: a collection of data comprising imagery and/or audio        components that capture a scene.    -   Viewing data: data that records aspects of viewing of an        experience by one or more viewers.    -   Viewing volume: a three-dimensional region from within which        virtual views of a scene maybe generated.    -   Viewpoint video: imagery and/or sound comprising one or more        virtual views.    -   Virtual reality: an immersive viewing experience in which images        presented to the viewer are based on the location and/or        orientation of the viewer's head and/or eyes.    -   Virtual view: a reconstructed view, typically for display in a        virtual reality or augmented reality headset, which may be        generated by resampling and/or interpolating data from a        captured light-field volume.    -   Virtual viewpoint: the location, within a coordinate system        and/or light-field volume, from which a virtual view is        generated.

In addition, for ease of nomenclature, the term “camera” is used hereinto refer to an image capture device or other data acquisition device.Such a data acquisition device can be any device or system foracquiring, recording, measuring, estimating, determining and/orcomputing data representative of a scene, including but not limited totwo-dimensional image data, three-dimensional image data, and/orlight-field data. Such a data acquisition device may include optics,sensors, and image processing electronics for acquiring datarepresentative of a scene, using techniques that are well known in theart. One skilled in the art will recognize that many types of dataacquisition devices can be used in connection with the presentdisclosure, and that the disclosure is not limited to cameras. Thus, theuse of the term “camera” herein is intended to be illustrative andexemplary, but should not be considered to limit the scope of thedisclosure. Specifically, any use of such term herein should beconsidered to refer to any suitable device for acquiring image data.

In the following description, several systems and methods for capturingvideo are described. One skilled in the art will recognize that thesevarious systems and methods can be performed singly and/or in anysuitable combination with one another. Further, many of theconfigurations and techniques described herein are applicable toconventional imaging as well as light-field imaging. Further, althoughthe ensuing description focuses on video capture for use in virtualreality or augmented reality, the systems and methods described hereinmay be used in a much wider variety of video applications.

Importance Metrics

As described previously, delivery of a virtual reality or augmentedreality experience may push the limits of bandwidth, storage, and/orprocessing capabilities of known computing and display systems.Accordingly, it is desirable to give priority, in terms of such systemresources, to the content that is most desirable and/or most likely tobe viewed by the viewer. This may be accomplished, in some embodiments,by assigning different importance metrics to different portions of videodata for a virtual reality or augmented reality experience. Theimportance metrics may denote which portions are most important, andtherefore should be prioritized for delivery to the viewer. Oneexemplary method for using such importance metrics will be shown anddescribed in connection with FIG. 1.

Referring to FIG. 1, a flow diagram depicts a method 100 for deliveringvideo for a virtual reality or augmented reality experience, accordingto one embodiment. As shown, the method 100 may start 110 with a step120 in which video data is stored. The video data may encompass videofrom multiple viewpoints and/or viewing directions within a viewingvolume that can be selectively delivered to the viewer based on theposition and/or orientation of the viewer's head within the viewingvolume, thus providing an immersive experience for the viewer.

The video data may be divided into a plurality of vantages, each ofwhich is for one of a plurality of positions within the viewing volume.Each vantage may be divided into a plurality of tiles, each of which isfor one of a plurality of possible viewing directions. Vantages andtiles will be described in greater subsequently, and are also describedin the above-cited related U.S. application Ser. No. 15/590,877 for“Spatial Random Access Enabled Video System with a Three-DimensionalViewing Volume,” filed on May 9, 2017, the disclosure of which isincorporated herein by reference in its entirety.

In a step 130, importance metrics may be assigned to different portionsof the video data. For example, the video data may be broken down intodifferent regions within the viewing volume, some of which receivehigher priority than others. Additionally or alternatively, the videodata may be broken down into different sets of tiles, representingdifferent viewing directions. The regions and/or sets of tiles may bedetermined based one or more factors, which may include, but are notlimited to, the following:

-   -   The likelihood that the viewer will position his or her head in        the region and/or orient his or her head along the viewing        direction;    -   The locations of any points of interest likely to be visited by        the viewer, including but not limited to featured portions of a        virtual reality experience and real-life locations likely to be        of interest in an augmented reality experience;    -   The quality of the experience as viewable from within the region        and/or from along the viewing direction, which may include        factors such as the visual quality of the content, the degree of        parallax, the level of interactivity for augmented reality        experience, and the like; and    -   The presence or absence of additional sensory content, such as        an auditory, olfactory, or tactile stimulus coordinated with the        region and/or along the viewing direction.

The determination of the importance metric for any given region and/orset of tiles may be made, for example, through the use of one or moreapproaches including, but not limited to:

-   -   Viewing data obtained from historical viewings of the        experience, indicating that viewers prefer or more frequently        one region and/or set of tiles over another;    -   Receipt of input from a user, such as a viewer or director,        setting importance metrics for one or more regions and/or tile        sets; and    -   Analysis of the video data to determine the quality and/or        likelihood of viewing of a given region and/or set of tiles.

These approaches will each be described in greater detail below.

In order to capture viewing data, the movement of a viewer's head may bemeasured as he or she views a particular segment of the experience.Viewing position and/or direction may be tracked and logged as theviewer experiences the segment. Where the video data is divided intovantages and/or tiles, the particular vantage and/or tile beingdelivered to the viewer may be logged.

Less frequently viewed vantages and/or tiles may receive a lesserimportance metric (an importance metric indicating they are lessimportant than other vantages and/or tiles). Based on the lesserimportance metric, these vantages and/or tiles may be compressed withlesser quality, delivered after other vantages and/or tiles, processedafter other vantages and/or tiles, omitted from the experiencealtogether, and/or otherwise de-prioritized in the delivery of theexperience.

If desired, the actions of the same and/or different viewers may bemeasured across time and/or across multiple viewings to determinebehavior. It is likely that a viewer will look at different places ontheir second or third viewing of the same content. Viewing statistics,such as vantage and/or tile viewing statistics, may be gathered offlineand/or online to inform the compression algorithm and/or other modulesthat control the capture, storage, delivery, and/or processing of theexperience.

Some viewers may have a special preference for a particular actor,athlete, or other performer in a sports broadcast, movie, concert, orother event. Compression quality and/or other delivery parameters may beset for the viewer based on his or her preferences. This may be doneautomatically by observing the viewing actions taken by the viewer.

In the alternative, explicit input may be received from the viewer toindicate such preferences. For example, the viewer may select particularperformers, particular types of scenes, particular portions of anexperience, and/or other aspects of an experience to be prioritized orde-prioritized for viewing.

In some examples, the viewer may explicitly select regions of theexperience to be prioritized. A testing method such as A/B testing maybe used to determine which resource allocation parameters provide thebest experience for the viewer.

According to still other embodiments, a content producer or other personinvolved with the generation of the experience may provide input toexplicitly assign importance metrics. For example, a director mayindicate the most optimal or intended viewing experience and assignhigher importance metrics to those vantage tile paths. This may be usedto drive the viewer to the path chosen by the director. Thus, importancemetrics may be used to subtly encourage viewers to view the content asindicated by the director.

In some embodiments, importance metrics may be assigned based on thepresence or absence of additional sensory content. Such additionalsensory content may include, but is not limited to, sounds, smells,tactile content such as haptic feedback or other vibrations, and thelike. Such sensory content may be timed to coincide with a key portionof the video data, which may have a high likelihood of being viewed by aviewer, or may desirably be rendered with higher quality. Such sensorycontent may further provide an impulse to the viewer to look in aparticular direction, strengthening the likelihood that the associatedvideo data will be viewed by the viewer.

As another alternative, the video data may be analyzed, for example, bya computing device, to automatically set importance metrics. Theimportance metrics may be calculated using one or more objectivemeasures. Such objective measures may be computed using attributes suchas, but not limited to, the following:

-   -   Pixel coverage of the three-dimensional scene, for example, as        in Vázquez, P. P., Feixas, M., Sbert, M. and Heidrich, W.        (2003), Automatic View Selection Using Viewpoint Entropy and its        Application to Image-Based Modelling. Computer Graphics Forum,        22: 689-300. doi:10.1111/j.1467-8659.2003.00717.x;    -   Quality metrics, such as PSNR, SSIM, for example, as in Wang,        Zhou, et al. “Image quality assessment: from error visibility to        structural similarity.” IEEE transactions on image processing        13.4 (2004): 200-612, AQM, for example, as in Myszkowski, Karol,        Przemyslaw Rokita, and Takehiro Tawara. “Perception-based fast        rendering and antialiasing of walkthrough sequences.” IEEE        Transactions on Visualization and Computer Graphics 6.4 (2000):        360-379, and absolute differences;    -   Saliency, for example, as in Itti, Laurent, Christof Koch, and        Ernst Niebur. “A model of saliency-based visual attention for        rapid scene analysis.” IEEE Transactions on pattern analysis and        machine intelligence 20.11 (1998): 1254-1259 or Lee, Chang Ha,        Amitabh Varshney, and David W. Jacobs. “Mesh saliency.”ACM        transactions on graphics (TOG). Vol. 24. No. 3. ACM, 2005;    -   Contrast sensitivity analysis, for example, as in Robson, J. G.        “Spatial and temporal contrast-sensitivity functions of the        visual system.” Josa 56.8 (1966): 1141-1142;    -   Image entropy; and    -   Motion.

The importance metric may be calculated in a wide variety of ways,through the use of data obtained from any of the foregoing methods. Suchmethods may be carried out across the vantages of the video data bycomparing vantages with each other, and/or across the tiles of one ormore vantage by comparing the tiles of each vantage with each other. Forexample, for a given tile, the importance metric may be calculated asthe change in quality measure when resource allocation parameters of thegiven tile are changed. One can also formulate the resource allocationas an optimization problem with the importance metrics as the objectivefunction and the resource allocation parameters as the input parameters,constraining by available system resources. Such optimization may becarried out as set forth in Everett III, Hugh. “Generalized Lagrangemultiplier method for solving problems of optimum allocation ofresources.” Operations research 11.3 (1963): 399-417.

Importance metrics may be in any of a variety of forms, including butnot limited to:

-   -   Numeric scores such as one through ten, which may be rounded to        the nearest integer or expressed as a floating point number;    -   Importance categories such as least important, moderately        important, and most important; and    -   Letter scores, such as a, b, c, and d.

Importance metrics may assign vantages and/or tiles to two categoriessuch as “more important” and “less important.” Alternatively, more thantwo distinct importance metrics may be assignable to provide a broaderspectrum of importance levels. Importance metrics may be stored inassociation with the video data, for example, in metadata stored infiles of the video data.

In some embodiments, the step 130 may be carried out prior to the step120, and the step 120 may then be carried out with reference to theimportance metrics of the video data. For example, some or all of thevideo data may be compressed, and the compression used for vide datawith a high importance metric may be different from that of the videodata with a low importance metric. Specifically, the video data with ahigher importance metric may be encoded and/or compressed in a mannerthat provides higher quality, faster retrieval, faster processing,and/or the like, by comparison with the video data with a lowerimportance metric.

Additionally or alternatively, the video data may be captured in amanner that references the importance metrics. For example, more videodata may be captured proximate locations of interest in the immersiveexperience, or the video data captured may be captured at higher qualityat those locations. This may enhance the quality of the video data thatis available for generation of virtual viewpoints proximate thelocations of interest.

Once the importance metrics have been assigned to the video data, thevirtual reality or augmented reality experience may be initiated. In astep 140, viewpoint data may be received to indicate the position and/ororientation of the viewer's head, indicating the viewer's actualviewpoint. The actual viewpoint may be converted into a virtualviewpoint within the viewing volume of the video data.

In a step 150, a subset of the video data may be retrieved. The subsetmay be selected to include all of the video data likely to be needed torender a virtual view of the scene captured by the video data, from thevirtual viewpoint corresponding to the viewpoint data received in thestep 140. The contents of the subset may be determined based, in part,on the importance metrics; video data corresponding to particularvantages and/or tiles may optionally be excluded from the subset if theimportance metric for those vantages and/or tiles is below a threshold.Additionally or alternatively, the order in which the video data withinthe subset is retrieved may be determined based on the importancemetrics, with the video data within the subset having lower importancemetrics retrieved after that having higher importance metrics.

In a step 160, the subset of the video data retrieved in the step 150may be used to generate viewpoint video data, representing a view of thescene from the viewer's viewpoint. Generation of the viewpoint video mayalso be carried out with reference to the importance metrics. Forexample, decompression of the portion of the subset having a higherimportance metric may be carried out before and/or with higher qualitythan decompression of the portion of the subset having a lowerimportance metric. Additionally or alternatively, the portion of thesubset with a higher importance metric may be rendered for viewingbefore and/or with higher quality than rendering of the portion of thesubset having a lower importance metric.

In a step 170, the viewpoint video may be displayed for the viewer on adisplay device. In some embodiments, the display device may be part of avirtual reality or augmented reality headset. The viewpoint video mayinclude sound, which may be played for the viewer via an output devicesuch as one or more speakers or headphones. As indicated previously, theexperience may additional sensory content such as sounds, smells,tactile content, and the like. If desired, virtual reality or augmentedreality equipment may include other output devices, such as vibration orscent-producing elements, that provide such additional sensory content.

Pursuant to a query 180, a determination may be made as to whether theexperience has been completed. If not, the method 100 may return to thestep 140, in which the viewpoint data may again be captured to obtainthe position and/or orientation for a new virtual viewpoint from whichthe scene is to be rendered for display for the viewer. The step 140,the step 150, the step 160, and the step 170 may be repeated until thequery 180 is answered in the affirmative, representing that theexperience is complete. The method 100 may then end 190.

The steps of the method 100 may be reordered, omitted, replaced withalternative steps, and/or supplemented with additional steps notspecifically described herein. The steps set forth above will bedescribed in greater detail subsequently in the discussion of vantagesand tiles.

Virtual Reality Display

Referring to FIG. 2, a screenshot diagram 200 depicts a frame from aviewpoint video of a virtual reality experience, according to oneembodiment. As shown, the screenshot diagram 200 depicts a left headsetview 210, which may be displayed for the viewer's left eye, and a rightheadset view 220, which may be displayed for the viewer's right eye. Thedifferences between the left headset view 210 and the right headset view220 may provide a sense of depth, enhancing the viewer's perception ofimmersion in the scene.

Vantages

As indicated previously, the video data for a virtual reality oraugmented reality experience may be divided into a plurality ofvantages, each of which represents the view from one location in theviewing volume. More specifically, a vantage is a view of a scene from asingle point in three-dimensional space. A vantage can have any desiredfield-of-view (e.g. 90° horizontal×90° vertical, or 360° horizontal×180°vertical) and pixel resolution. A viewing volume may be populated withvantages in three-dimensional space at some density.

Based on the position of the viewer's head, which may be determined bymeasuring the position of the headset worn by the viewer, the system mayinterpolate from a set of vantages to render the viewpoint video in theform of the final left and right eye view, such as the left headset view210 and the right headset view 220 of FIG. 2. A vantage may containextra data such as depth maps, edge information, and/or the like toassist in interpolation of the vantage data to generate the viewpointvideo.

The vantage density may be uniform throughout the viewing volume, or maybe non-uniform. A non-uniform vantage density may enable the density ofvantages in any region of the viewing volume to be determined based onthe likelihood the associated content will be viewed, the quality of theassociated content, and/or the like. Thus, if desired, importancemetrics may be used to establish vantage density for any given region ofa viewing volume.

Referring to FIG. 3, a screenshot diagram 300 depicts the screenshotdiagram 200 of FIG. 2, overlaid with a viewing volume 310 for each ofthe eyes, according to one embodiment. Each viewing volume 310 maycontain a plurality of vantages 320, each of which defines a point inthree-dimensional space from which the scene may be viewed by theviewer. Viewing from between the vantages 320 may also be carried out bycombining and/or extrapolating data from vantages 320 adjacent to theviewpoint.

Referring to FIG. 4, a screenshot diagram 400 depicts the view after theheadset has been moved forward, toward the scene of FIG. 2, according toone embodiment. Again, a left headset view 410 and a right headset view420 are shown, with the vantages 320 of FIG. 3 superimposed. Further,for each eye, currently and previously traversed vantages 430 arehighlighted, as well as the current viewing direction 440.

Tiles

Referring to FIG. 5, a screenshot diagram 500 depicts the color channelfrom a single vantage, such as one of the vantages 320 of FIG. 3,according to one embodiment. As shown, each vantage 320 may have a wideangle field-of-view of the scene, encompassing many possible viewingdirections. For a full 360° horizontal×180° vertical vantage, the vieweris only looking at a certain portion of vantage at any given time. Theportion may be defined by the headset's field-of-view for each eye.

To be efficient for rendering performance, data input/outputperformance, and/or data compression/decompression, vantages may betiled into smaller areas. Uniformly-sized rectangular tiles may be usedin some embodiments. For example, as depicted in FIG. 5, the colorchannel for one of the vantages 320 may be divided into a rectangulargrid of tiles 520, with thirty-two columns of tiles, and sixteen rows oftiles. This is merely exemplary, as different numbers of tiles may beused, such as sixteen columns by eight rows. The tiles 520 are alsodepicted in rectilinear space, but may, in alternative embodiments, bedefined in the latitudinal/longitudinal space defined by wrapping thescreenshot diagram 500 around a sphere.

Referring to FIG. 12, a diagram 1200 depicts a vantage 1210 according toone embodiment. The vantage 1210 may have a center 1220 and image data,such as an RGB channel and/or a depth channel, which may define a sphere1230 encircling the center 1220. A field-of-view may be represented byfour vectors 1240 extending outward from the center 1220 to pass throughthe surface of the sphere 1230. A semispherical area 1250 (shown in redhatching) on the surface of the sphere 1230, between the locations atwhich the vectors 1240 pass through the surface of the sphere 1230, mayrepresent the portion of the RGB channel of the vantage 1210 that is tobe viewed currently and/or used in combination with other vantage datato generate viewpoint video.

Referring to FIG. 6, a diagram 600 depicts the manner in which the tilesof a vantage, such as one of the vantages 320 of FIG. 3, may beselected, according to one embodiment. The vantages 320 have any of awide variety of shapes, including but not limited to spherical andcylindrical shapes. The diagram 600 depicts vantages 320 as havingspherical shapes, by way of example.

The top row depicts four side views of a sphere representing the vantage320. A field-of-view 610 is oriented along the viewing direction 620currently being viewed by the viewer. The field-of-view 610 is depictedin the same orientation in each view of the top row because thefield-of-view 610 is depicted, in each case, from its left side. Themiddle row depicts four top views of the sphere representing the vantage320, depicting the field-of-view 610 in various orientations.

The bottom row depicts the color channel 630 for the vantage 320,divided into tiles as in FIG. 5. A subset 640 of the tiles of the colorchannel 630 may be fetched to correspond to the viewer's viewpoint,permitting the viewpoint video to be rendered. The subset 640 may move,for example, to the right, within the color channel 630, as the viewerpivots his or her head to the right, as can be seen by viewing the firstrow, then the second row, then the third row, and then the fourth row ofFIG. 6. Tiles may also be fetched from other vantages proximate theviewers viewpoint and combined with the subset 640 to render theviewpoint video.

In alternative embodiments, non-uniformly sized and/or non-rectangulartiles may be used. The sizes and/or shapes of the tiles may be dependenton the content depicted in those tiles. For example, more tiles may bepositioned areas of vantages with higher importance metrics than thesurrounding areas, enabling the more important viewing directions to berendered in greater detail.

Depth Channel

Referring to FIG. 7, a screenshot diagram 700 depicts the depth channelfrom the vantage used to provide the screenshot diagram 500 of FIG. 5,according to one embodiment. Depth information may be encoded into eachvantage to provide proper parallax and/or other visual effects.

Vantage-Based and Tile-Based Usage of Importance Metrics

As indicated previously, vantages, such as the vantages 320 of FIG. 3,may have different importance metrics to indicate the relativeimportance of the vantages 320. Further, tiles, such as the tiles 520 ofFIG. 5, can have different importance metrics indicating the relativeimportance of the tiles. The importance metrics may be used in a varietyof ways to prioritize and/or enhance delivery of more important contentto the viewer.

In some embodiments, the importance metrics may be used to guide thecompression algorithms to allocate more bits/quality to the moreimportant portions and less bits/quality to the less important portionsof the viewpoint provided by a vantage 320. As each of the tiles 520represents a direction into the scene as well as a position in space,importance levels of tiles may vary along either or both of the X and Yaxes.

Such importance metrics may guide a vantage-based video system in theallocation of resources such as, but not limited to, the number ofvantages, vantage density, vantage placement, bits and encoding/decodingcomplexity, in order to meet system constraints, such as bandwidth,storage, CPU resources, and/or GPU resources.

For example, to maximize perceived quality, the system can allocate moreresources to more important regions of the viewing volume and/or moreimportant tiles than less important regions and/or tiles. If a limit onthe maximal number of vantage must be adhered to in order to meet systemrequirements, the importance metrics may be used to determine theoptimal location of the vantages. Thus, importance metrics may be usedto place vantages or tiles in the video data in the step 120 of themethod 100 of FIG. 1.

The importance metric for vantage tiles may be applied to cachingstrategy for playback, for example, on a personal computer or mobiledevice. In such applications, where disk input/output and/or networkstreaming bandwidth may be constrained, it may be desirable to pre-fetchthe most important vantage tiles ahead of time. Any number of knownpredictive caching techniques may be used to accomplish this. Theimportance metrics may be referenced to prioritize more important videodata for predictive caching.

A system can utilize an importance map to allocate system resources forcapturing, encoding, decoding, storing, pre-processing, post-processing,delivering, and/or playing content. The parameters used for resourceallocation may include, but are not limited to the following, and may beapplied to each individual tile or vantage, a subset of tiles orvantages and/or globally:

-   -   The number of vantages in the viewing volume and/or a region of        the viewing volume;    -   Vantage density in the viewing volume and/or a region of the        viewing volume;    -   The position of vantages relative to content;    -   The location of vantages;    -   The number, complexity, and location of view-dependent        variations, such as variations in lighting and resolution;    -   The spatial resolution of tiles;    -   The temporal resolution of tiles;    -   The color/depth bit-sampling of tiles;    -   The bitrate of tiles;    -   The quality and/or rate of rendering;    -   The number of vantages used for generating a viewpoint;    -   The density of meshes, for example, for rendered        three-dimensional models;    -   The density of cameras used to capture the scene;    -   The manner in which various portions of the video data are        prioritized (which portions of the video data to process, store,        render, and/or transmit when resources are constrained);    -   The extent of pre-processing to be carried out for various        portions of the video data; and    -   Other codec-related parameters used for encoding/decoding image        data.

Those of skill in the art will recognize that the list set forth aboveis merely exemplary. The parameters listed above may be modified singlyor in combination with each other. In other embodiments, other systemresource parameters may be modified based on the importance metrics ofthe corresponding video data.

Vantage Density and Position

The density with which vantages are arranged (uniformly ornon-uniformly) within a viewing volume, or a region of a viewing volume,may be an important resource allocation parameter. Based on howimportant a particular vantage and/or tile is, more vantages can beallocated to that region of the viewing volume. Optimal positions may befound to cover disocclusions that may be very content-dependent and/orscene-dependent. Parallax and view-dependent lighting may be taken intoaccount in the assignment of importance metrics, since having thecorrect vantage density and position may greatly enhance provision ofparallax and view dependent lighting.

Referring to FIG. 8, a diagram 800 depicts a portion of a scene in whichtwo objects 810 are positioned such that an occluded area 820 existsbehind the objects 810, according to one embodiment. A keyhole 830 mayexist between the objects 810, through which the occluded area 820 maybe viewable from a viewing volume 840. A plurality of vantages 850 witha viewing volume 840 are positioned proximate the objects 810. Thevantages 850 may be cylindrical or spherical vantages, or may have anyother shape, as discussed in connection with FIG. 6.

None of the vantages 850 within the viewing volume 840 are aligned withthe keyhole 830, as shown by the fields-of-view 860 centered at thevantages 850 and oriented toward the objects 810. Accordingly, thecorresponding video data may not contain accurate imagery depicting theoccluded area 820. A viewer positioning his or head between the vantages850 in an attempt to view the occluded area 820 may view viewpoint videothat lacks detail regarding the occluded area 820 because the viewpointvideo may be generated based on the tiles from the vantages 850; none ofthese tiles effectively depicts the occluded area 820.

Referring to FIG. 9, a diagram 900 depicts the portion of the scene ofFIG. 9, in which another vantage 950 has been added to enhance viewingof the occluded area 820, according to one embodiment. A field-of-view960 from the vantage 950, oriented toward the keyhole 830, enables theviewer to view a portion of the occluded area 820.

This illustration of keyhole disocclusion depicts one manner in whichvantage density and/or placement may help to determine the quality ofthe viewing experience. Each additional vantage adds to the quantity ofvideo data that needs to be stored, retrieved, and/or processed;accordingly, it is beneficial to conserve system resources by using asmaller vantage density for less important portions of the video data.

One method of optimizing vantage density and position is for contentcreators to place vantages manually and adjust them based on quickfeedback. A fixed vantage density may initially be used, and the outputmay be viewed in a virtual reality headset. Then, the vantages may bemanually moved and adjusted vantages, either singly or in groups, untilthe final output quality is satisfactory. This process may be repeatedfor each frame in time.

To save editing time, the content creator may “pin” a set of vantages toa particular region of the viewing volume. Optical flow methods and/orthe like may be applied to track these regions over time to provide thecontent creators with a better starting set of vantage positions. Thismay reduce the amount of editing that needs to be done.

Another method is to place the vantages automatically using a softwarealgorithm that analyzes the scene and generates the optimal vantagedensity and/or position for the final output. In some embodiments, amixture of the two methods (manual and automated vantage placement) maybe carried out. For example, the automated method may generate astarting vantage placement for each frame. The content creator may makefurther adjustments in each frame, if necessary.

Viewing Data

As mentioned above, viewing data may be collected and used to setimportance metrics. The viewing data may come from viewing by thecontent creator to set vantage densities and/or positions, as set forthin the preceding section. Alternatively, the viewing data may come fromother viewers (such as consumers who are unaffiliated with the contentcreator) who view the experience subsequent to its creation, asdescribed in the description of FIG. 1. The viewing data may be used notjust to set vantage position and/or density, but also to set any of thesystem resource parameters listed previously.

Referring to FIG. 10, a screenshot diagram 1000 depicts the vantages1010 traversed by a single viewer and accumulated over time, accordingto one embodiment. The vantages 1010 traversed by the viewer may beassigned higher importance metrics, relative to the importance metricsassigned to vantages that the viewer did not traverse.

In some embodiments, other aspects of viewing data may be recorded inconnection with the information presented in FIG. 10. For example, thenumber of times a vantage was traversed by the viewer, the amount oftime the viewer spent traversing each vantage, and/or viewing data forparticular tiles of the vantages 1010 may be recorded and factored intothe importance metrics to be assigned.

In some embodiments, more explicit viewer feedback may also be receivedand recorded. For example, a viewer may fill out a survey indicatingwhich aspects of the virtual reality or augmented reality experiencewere the most enjoyable. Additionally or alternatively, biometric data(such as pulse rate, blood pressure, brain activity, etc.) may betracked to glean information regarding the viewer's level of engagementwith each portion of the experience.

In some examples, viewing data from multiple viewers may be recorded andaggregated to assign importance metrics. One such example will be shownand described in connection with FIG. 11.

Referring to FIG. 11, a screenshot diagram 1100 depicts the vantages1110 traversed by multiple viewers and accumulated over time, accordingto one embodiment. Vantages 1120 that have been viewed more frequentlyand/or for longer periods of time may be shown in a darker color,thereby presenting vantage viewing in the form of a “heat map.” This maybe extended in time so that changes over time in the volume and/or“heat” of the heat map may be visualized. Such information may be usedto facilitate assignment of the importance metrics.

The above description and referenced drawings set forth particulardetails with respect to possible embodiments. Those of skill in the artwill appreciate that the techniques described herein may be practiced inother embodiments. First, the particular naming of the components,capitalization of terms, the attributes, data structures, or any otherprogramming or structural aspect is not mandatory or significant, andthe mechanisms that implement the techniques described herein may havedifferent names, formats, or protocols. Further, the system may beimplemented via a combination of hardware and software, as described, orentirely in hardware elements, or entirely in software elements. Also,the particular division of functionality between the various systemcomponents described herein is merely exemplary, and not mandatory;functions performed by a single system component may instead beperformed by multiple components, and functions performed by multiplecomponents may instead be performed by a single component.

Reference in the specification to “one embodiment” or to “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiments is included in at least oneembodiment. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment.

Some embodiments may include a system or a method for performing theabove-described techniques, either singly or in any combination. Otherembodiments may include a computer program product comprising anon-transitory computer-readable storage medium and computer programcode, encoded on the medium, for causing a processor in a computingdevice or other electronic device to perform the above-describedtechniques.

Some portions of the above are presented in terms of algorithms andsymbolic representations of operations on data bits within a memory of acomputing device. These algorithmic descriptions and representations arethe means used by those skilled in the data processing arts to mosteffectively convey the substance of their work to others skilled in theart. An algorithm is here, and generally, conceived to be aself-consistent sequence of steps (instructions) leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical, magnetic or optical signals capable of being stored,transferred, combined, compared and otherwise manipulated. It isconvenient at times, principally for reasons of common usage, to referto these signals as bits, values, elements, symbols, characters, terms,numbers, or the like. Furthermore, it is also convenient at times, torefer to certain arrangements of steps requiring physical manipulationsof physical quantities as modules or code devices, without loss ofgenerality.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the following discussion,it is appreciated that throughout the description, discussions utilizingterms such as “processing” or “computing” or “calculating” or“displaying” or “determining” or the like, refer to the action andprocesses of a computer system, or similar electronic computing moduleand/or device, that manipulates and transforms data represented asphysical (electronic) quantities within the computer system memories orregisters or other such information storage, transmission or displaydevices.

Certain aspects include process steps and instructions described hereinin the form of an algorithm. It should be noted that the process stepsand instructions of described herein can be embodied in software,firmware and/or hardware, and when embodied in software, can bedownloaded to reside on and be operated from different platforms used bya variety of operating systems.

Some embodiments relate to an apparatus for performing the operationsdescribed herein. This apparatus may be specially constructed for therequired purposes, or it may comprise a general-purpose computing deviceselectively activated or reconfigured by a computer program stored inthe computing device. Such a computer program may be stored in acomputer readable storage medium, such as, but is not limited to, anytype of disk including floppy disks, optical disks, CD-ROMs,magnetic-optical disks, read-only memories (ROMs), random accessmemories (RAMs), EPROMs, EEPROMs, flash memory, solid state drives,magnetic or optical cards, application specific integrated circuits(ASICs), and/or any type of media suitable for storing electronicinstructions, and each coupled to a computer system bus. Further, thecomputing devices referred to herein may include a single processor ormay be architectures employing multiple processor designs for increasedcomputing capability.

The algorithms and displays presented herein are not inherently relatedto any particular computing device, virtualized system, or otherapparatus. Various general-purpose systems may also be used withprograms in accordance with the teachings herein, or it may proveconvenient to construct more specialized apparatus to perform therequired method steps. The required structure for a variety of thesesystems will be apparent from the description provided herein. Inaddition, the techniques set forth herein are not described withreference to any particular programming language. It will be appreciatedthat a variety of programming languages may be used to implement thetechniques described herein, and any references above to specificlanguages are provided for illustrative purposes only.

Accordingly, in various embodiments, the techniques described herein canbe implemented as software, hardware, and/or other elements forcontrolling a computer system, computing device, or other electronicdevice, or any combination or plurality thereof. Such an electronicdevice can include, for example, a processor, an input device (such as akeyboard, mouse, touchpad, trackpad, joystick, trackball, microphone,and/or any combination thereof), an output device (such as a screen,speaker, and/or the like), memory, long-term storage (such as magneticstorage, optical storage, and/or the like), and/or network connectivity,according to techniques that are well known in the art. Such anelectronic device may be portable or nonportable. Examples of electronicdevices that may be used for implementing the techniques describedherein include: a mobile phone, personal digital assistant, smartphone,kiosk, server computer, enterprise computing device, desktop computer,laptop computer, tablet computer, consumer electronic device,television, set-top box, or the like. An electronic device forimplementing the techniques described herein may use any operatingsystem such as, for example: Linux; Microsoft Windows, available fromMicrosoft Corporation of Redmond, Wash.; Mac OS X, available from AppleInc. of Cupertino, Calif.; iOS, available from Apple Inc. of Cupertino,Calif.; Android, available from Google, Inc. of Mountain View, Calif.;and/or any other operating system that is adapted for use on the device.

In various embodiments, the techniques described herein can beimplemented in a distributed processing environment, networked computingenvironment, or web-based computing environment. Elements can beimplemented on client computing devices, servers, routers, and/or othernetwork or non-network components. In some embodiments, the techniquesdescribed herein are implemented using a client/server architecture,wherein some components are implemented on one or more client computingdevices and other components are implemented on one or more servers. Inone embodiment, in the course of implementing the techniques of thepresent disclosure, client(s) request content from server(s), andserver(s) return content in response to the requests. A browser may beinstalled at the client computing device for enabling such requests andresponses, and for providing a user interface by which the user caninitiate and control such interactions and view the presented content.

Any or all of the network components for implementing the describedtechnology may, in some embodiments, be communicatively coupled with oneanother using any suitable electronic network, whether wired or wirelessor any combination thereof, and using any suitable protocols forenabling such communication. One example of such a network is theInternet, although the techniques described herein can be implementedusing other networks as well.

While a limited number of embodiments has been described herein, thoseskilled in the art, having benefit of the above description, willappreciate that other embodiments may be devised which do not departfrom the scope of the claims. In addition, it should be noted that thelanguage used in the specification has been principally selected forreadability and instructional purposes, and may not have been selectedto delineate or circumscribe the inventive subject matter. Accordingly,the disclosure is intended to be illustrative, but not limiting.

What is claimed is:
 1. A method for delivering video for a virtualreality or augmented reality experience, the method comprising: at adata store, storing video data for a virtual reality or augmentedreality experience, the video data comprising a first portion having afirst importance metric and a second portion having a second importancemetric, the first importance metric and the second importance metricbeing based on viewing data, the viewing data being one of: historicalviewings of the virtual reality or augmented reality experienceindicating a set of portions of the virtual reality or augmented realityexperience having been viewed by more viewers than other portions of thevirtual reality or augmented reality experience, or a user input beingindicative of a plurality of portions corresponding to a set of stimulipresented as a part of the virtual reality or augmented realityexperience; at a processor, receiving viewpoint data indicative of aposition and/or an orientation of a viewer's viewpoint; at theprocessor, retrieving a subset of the video data from the data store,the subset comprising at least the first portion of the video data; atthe processor, using the subset to generate viewpoint video of thevirtual reality or augmented reality experience, from a virtualviewpoint corresponding to the viewer's viewpoint; and on a displaydevice, displaying the viewpoint video; wherein a difference existsbetween the first importance metric and the second importance metric,the difference denoting that viewing of the first portion is more likelyand/or preferential to viewing of the second portion; and whereinperforming one step selected from the group consisting of storing thevideo data, retrieving the subset, and using the subset to generate theview-point video comprises, based on the difference, expediting and/orenhancing performance of the step for the first portion, relative to thesecond portion.
 2. The method of claim 1, wherein: the video datacomprises a plurality of vantage video data sets, each of whichrepresents a view from one of a plurality of vantages within a viewingvolume; the virtual viewpoint is within the viewing volume; theviewpoint data is indicative of the position of the viewer's viewpoint;and using the subset to generate the viewpoint video comprises using oneor more of the vantage video data sets for one or more of the vantagespositioned proximate the virtual viewpoint.
 3. The method of claim 2,wherein: the first portion comprises a first vantage video data set ofthe vantage video data sets, the first vantage video data setrepresenting a view from a first vantage of the plurality of vantages;the second portion comprises a second vantage video data set of thevantage video data sets, the second vantage video data set representinga view from a second vantage of the plurality of vantages; and the firstimportance metric denotes that the first vantage video data set is morelikely to be included in the subset than the second vantage video dataset.
 4. The method of claim 2, wherein: the first portion represents oneor more views from within a first region of the viewing volume; thesecond portion represents one or more views from within a second regionof the viewing volume; and expediting and/or enhancing performance ofthe step for the first portion, relative to the second portion,comprises storing the video data such that at least one of a number ofvantages, a density of vantages, locations of vantages, a number ofvantages used to generate the viewpoint video, lighting applied tovantages, and resolution of vantages is enhanced within the firstregion, relative to the second region.
 5. The method of claim 2,wherein: each of the vantage video data sets comprises a plurality oftiles, each representing a view from a corresponding vantage of theplurality of vantages, along a viewing direction; the viewpoint data isfurther indicative of the orientation* of the viewer's viewpoint; andusing the subset to generate the viewpoint video comprises using one ormore of the tiles, with one or more viewing directions corresponding tothe orientation, for each of the one or more of the vantages positionedproximate the virtual viewpoint.
 6. The method of claim 5, wherein: thefirst portion comprises a first tile of the plurality of tiles of afirst vantage video data set of the vantage vide data sets, the firsttile representing a view from a first vantage of the plurality ofvantages, along a first viewing direction; the second portion comprisesa second tile of the plurality of tiles of the first vantage video dataset, the second tile representing a view from the first vantage, along asecond viewing direction different from the first viewing direction; andthe first importance metric denotes that the first tile is more likelyto be included in the subset than the second tile.
 7. The method ofclaim 5, wherein: the first portion represents a first set of tiles ofthe plurality of vantages, that are oriented along a first set ofviewing directions of the one or more viewing directions; the secondportion represents a second set of tiles of the plurality of vantages,that are oriented along a second set of viewing directions of the one ormore viewing directions; and expediting and/or enhancing performance ofthe step for the first portion, relative to the second portion,comprises storing the video data such that at least one of a tilespatial resolution, tile temporal resolution, tile color depth, and tilebit rate is enhanced for the first set of tiles, relative to the secondset of tiles.
 8. The method of claim 1, wherein: the subset comprisesthe first portion and the second portion of the video data; andexpediting and/or enhancing performance of the step for the firstportion, relative to the second portion, comprises retrieving the subsetof the video data such that the first portion is retrieved prior toretrieval of the second portion.
 9. The method of claim 1, wherein: thesubset comprises the first portion and the second portion of the videodata; and expediting and/or enhancing performance of the step for thefirst portion, relative to the second portion, comprises using thesubset to generate the viewpoint video such that a first segment of theviewpoint video incorporating the first portion of the video data isgenerated prior to generation of a second segment of the viewpoint videoincorporating the second portion of the video data.
 10. The method ofclaim 1, wherein: the subset comprises the first portion and the secondportion of the video data; and expediting and/or enhancing performanceof the step for the first portion, relative to the second portion,comprises using the subset to generate the viewpoint video such that afirst segment of the viewpoint video incorporating the first portion ofthe video data has a higher level of quality than a second segment ofthe viewpoint video incorporating the second portion of the video data.11. The method of claim 1, further comprising: at the data store,receiving viewing data indicating that one or more viewers prefer ormore frequently view the first portion of the video data over the secondportion of the video data; at the processor, based on the viewing data,assigning the first importance metric to the first portion of the videodata; and at the processor, based on the viewing data, assigning thesecond importance metric to the second portion of the video data. 12.The method of claim 1, further comprising: at an input device, receivinguser input indicating that viewing of the first portion is more likelyand/or preferential to viewing of the second portion; at the processor,based on the user input, assigning the first importance metric to thefirst portion of the video data; and at the processor, based on the userinput, assigning the second importance metric to the second portion ofthe video data.
 13. The method of claim 12, wherein: the user inputindicates that viewing of the first portion is more likely than viewingof the second portion; and the method further comprises, at an outputdevice distinct from the display device, delivering an olfactory ortactile stimulus to the viewer to prompt the viewer to position ororient the viewer's viewpoint in a manner that causes the first portionof the video data to be included in the subset.
 14. The method of claim1, further comprising: at the processor, carrying out analysis of one orboth of the video data and audio data that accompanies the video data todetermine that viewing of the first portion is more likely and/orpreferential to viewing of the second portion; at the processor, basedon the analysis, assigning the first importance metric to the firstportion of the video data; and at the processor, based on the analysis,assigning the second importance metric to the second portion of thevideo data.
 15. A non-transitory computer-readable medium for deliveringvideo for a virtual reality or augmented reality experience, comprisinginstructions stored thereon, that when executed by a processor, performthe steps of: causing a data store to store video data for a virtualreality or augmented reality experience, the video data comprising afirst portion having a first importance metric and a second portionhaving a second importance metric, the first importance metric and thesecond importance metric being based on viewing data, the viewing databeing one of: historical viewings of the virtual reality or augmentedreality experience indicating a set of portions of the virtual realityor augmented reality experience having been viewed by more viewers thanother portions of the virtual reality or augmented reality experience,or a user input being indicative of a plurality of portionscorresponding to a set of stimuli presented as a part of the virtualreality or augmented reality experience receiving viewpoint dataindicative of a position and/or an orientation of a viewer's viewpoint;retrieving a subset of the video data from the data store, the subsetcomprising at least the first portion of the video data; using thesubset to generate viewpoint video of the virtual reality or augmentedreality experience, from a virtual viewpoint corresponding to theviewer's viewpoint; and causing a display device to display theviewpoint video; wherein a difference exists between the firstimportance metric and the second importance metric, the differencedenoting that viewing of the first portion is more likely and/orpreferential to viewing of the second portion; and wherein performingone step selected from the group consisting of storing the video data,retrieving the subset, and using the subset to generate the view-pointvideo comprises, based on the difference, expediting and/or enhancingperformance of the step for the first portion, relative to the secondportion.
 16. The non-transitory computer-readable medium of claim 15,wherein: the video data comprises a plurality of vantage video datasets, each of which represents a view from one of a plurality ofvantages within a viewing volume; the virtual viewpoint is within theviewing volume; the viewpoint data is indicative of the position of theviewer's viewpoint; and using the subset to generate the viewpoint videocomprises using one or more of the vantage video data sets for one ormore of the vantages positioned proximate the virtual viewpoint.
 17. Thenon-transitory computer-readable medium of claim 16, wherein: the firstportion comprises a first vantage video data set of the vantage videodata sets, the first vantage video data set representing a view from afirst vantage of the plurality of vantages; the second portion comprisesa second vantage video data set of the vantage video data sets, thesecond vantage video data set representing a view from a second vantageof the plurality of vantages; and the first importance metric denotesthat the first vantage video data set is more likely to be included inthe subset than the second vantage video data set.
 18. Thenon-transitory computer-readable medium of claim 16, wherein: the firstportion represents one or more views from within a first region of theviewing volume; the second portion represents one or more views fromwithin a second region of the viewing volume; and expediting and/orenhancing performance of the step for the first portion, relative to thesecond portion, comprises storing the video data such that at least oneof a number of vantages, a density of vantages, locations of vantages, anumber of vantages used to generate the viewpoint video, lightingapplied to vantages, and resolution of vantages is enhanced within thefirst region, relative to the second region.
 19. The non-transitorycomputer-readable medium of claim 16, wherein: each of the vantage videodata sets comprises a plurality of tiles, each representing a view froma corresponding vantage of the plurality of vantages, along a viewingdirection; the viewpoint data is further indicative of the orientationof the viewer's viewpoint; and using the subset to generate theviewpoint video comprises using one or more of the tiles, with one ormore viewing directions corresponding to the orientation, for each ofthe one or more of the vantages positioned proximate the virtualviewpoint.
 20. The non-transitory computer-readable medium of claim 19,wherein: the first portion comprises a first tile of the plurality oftiles of a first vantage video data set of the vantage vide data sets,the first tile representing a view from a first vantage of the pluralityof vantages, along a first viewing direction; the second portioncomprises a second tile of the plurality of tiles of the first vantagevideo data set, the second tile representing a view from the firstvantage, along a second viewing direction different from the firstviewing direction; and the first importance metric denotes that thefirst tile is more likely to be included in the subset than the secondtile.
 21. The non-transitory computer-readable medium of claim 19,wherein: the first portion represents a first set of tiles of theplurality of vantages, that are oriented along a first set of viewingdirections of the one or more viewing directions; the second portionrepresents a second set of tiles of the plurality of vantages, that areoriented along a second set of viewing directions of the one or moreviewing directions; and expediting and/or enhancing performance of thestep for the first portion, relative to the second portion, comprisesstoring the video data such that at least one of a tile spatialresolution, tile temporal resolution, tile color depth, and tile bitrate is enhanced for the first set of tiles, relative to the second setof tiles.
 22. The non-transitory computer-readable medium of claim 15,wherein: the subset comprises the first portion and the second portionof the video data; and expediting and/or enhancing performance of thestep for the first portion, relative to the second portion, comprisesperforming at least one selection from the group consisting of:retrieving the subset of the video data such that the first portion isretrieved prior to retrieval of the second portion; using the subset togenerate the viewpoint video such that a first segment of the viewpointvideo incorporating the first portion of the video data is generatedprior to generation of a second segment of the viewpoint videoincorporating the second portion of the video data; and using the subsetto generate the viewpoint video such that a first segment of theviewpoint video incorporating the first portion of the video data has ahigher level of quality than a second segment of the viewpoint videoincorporating the second portion of the video data.
 23. Thenon-transitory computer-readable medium of claim 15, further comprisinginstructions stored thereon, that when executed by a processor, performthe steps of: causing the data store to receive viewing data indicatingthat one or more viewers prefer or more frequently view the firstportion of the video data over the second portion of the video data;based on the viewing data, assigning the first importance metric to thefirst portion of the video data; and based on the viewing data,assigning the second importance metric to the second portion of thevideo data.
 24. The non-transitory computer-readable medium of claim 15,further comprising instructions stored thereon, that when executed by aprocessor, perform the steps of: causing an input device to receive userinput indicating that viewing of the first portion is more likely and/orpreferential to viewing of the second portion; based on the user input,assigning the first importance metric to the first portion of the videodata; and processor, based on the user input, assigning the secondimportance metric to the second portion of the video data.
 25. Thenon-transitory computer-readable medium of claim 15, further comprisinginstructions stored thereon, that when executed by a processor, performthe steps of: carrying out analysis of one or both of the video data andaudio data that accompanies the video data to determine that viewing ofthe first portion is more likely and/or preferential to viewing of thesecond portion; based on the analysis, assigning the first importancemetric to the first portion of the video data; and based on theanalysis, assigning the second importance metric to the second portionof the video data.
 26. A system for delivering video for a virtualreality or augmented reality experience, the system comprising: a datastore configured to store video data for a virtual reality or augmentedreality experience, the video data comprising a first portion having afirst importance metric and a second portion having a second importancemetric, the first importance metric and the second importance metricbeing based on viewing data, the viewing data being one of: historicalviewings of the virtual reality or augmented reality experienceindicating a set of portions of the virtual reality or augmented realityexperience having been viewed by more viewers than other portions of thevirtual reality or augmented reality experience, or a user input beingindicative of a plurality of portions corresponding to a set of stimulipresented as a part of the virtual reality or augmented realityexperience a processor, communicatively connected to the data store,configured to: receive viewpoint data indicative of a position and/or anorientation of a viewer's viewpoint; retrieve a subset of the video datafrom the data store, the subset comprising at least the first portion ofthe video data; and use the subset to generate viewpoint video of thevirtual reality or augmented reality experience, from a virtualviewpoint corresponding to the viewer's viewpoint; and a display device,communicatively coupled to the processor, configured to display theviewpoint video; wherein a difference exists between the firstimportance metric and the second importance metric, the differencedenoting that viewing of the first portion is more likely and/orpreferential to viewing of the second portion; and wherein the datastore and/or the processor are further configured to perform one stepselected from the group consisting of storing the video data, retrievingthe subset, and using the subset to generate the viewpoint video by,based on the difference, expediting and/or enhancing performance of thestep for the first portion, relative to the second portion.
 27. Thesystem of claim 26, wherein: the video data comprises a plurality ofvantage video data sets, each of which represents a view from one of aplurality of vantages within a viewing volume; the virtual viewpoint iswithin the viewing volume; the viewpoint data is indicative of theposition of the viewer's viewpoint; and the processor is furtherconfigured to use the subset to generate the viewpoint video by usingone or more of the vantage video data sets for one or more of thevantages positioned proximate the virtual viewpoint.
 28. The system ofclaim 27, wherein: the first portion comprises a first vantage videodata set of the vantage video data sets, the first vantage video dataset representing a view from a first vantage of the plurality ofvantages; the second portion comprises a second vantage video data setof the vantage video data sets, the second vantage video data setrepresenting a view from a second vantage of the plurality of vantages;and the first importance metric denotes that the first vantage videodata set is more likely to be included in the subset than the secondvantage video data set.
 29. The system of claim 27, wherein: the firstportion represents one or more views from within a first region of theviewing volume; the second portion represents one or more views fromwithin a second region of the viewing volume; and the processor and/orthe data store are further configured to expedite and/or enhanceperformance of the step for the first portion, relative to the secondportion, by storing the video data such that at least one of a number ofvantages, a density of vantages, locations of vantages, a number ofvantages used to generate the viewpoint video, lighting applied tovantages, and resolution of vantages is enhanced within the firstregion, relative to the second region.
 30. The system of claim 27,wherein: each of the vantage video data sets comprises a plurality oftiles, each representing a view from a corresponding vantage of theplurality of vantages, along a viewing direction; the viewpoint data isfurther indicative of the orientation of the viewer's viewpoint; and theprocessor is further configured to use the subset to generate theviewpoint video by using one or more of the tiles, with one or moreviewing directions corresponding to the orientation, for each of the oneor more of the vantages positioned proximate the virtual viewpoint. 31.The system of claim 30, wherein: the first portion comprises a firsttile of the plurality of tiles of a first vantage video data set of thevantage vide data sets, the first tile representing a view from a firstvantage of the plurality of vantages, along a first viewing direction;the second portion comprises a second tile of the plurality of tiles ofthe first vantage video data set, the second tile representing a viewfrom the first vantage, along a second viewing direction different fromthe first viewing direction; and the first importance metric denotesthat the first tile is more likely to be included in the subset than thesecond tile.
 32. The system of claim 30, wherein: the first portionrepresents a first set of tiles of the plurality of vantages, that areoriented along a first set of viewing directions of the one or moreviewing directions; the second portion represents a second set of tilesof the plurality of vantages, that are oriented along a second set ofviewing directions of the one or more viewing directions; and theprocessor and/or the data store are further configured to expediteand/or enhance performance of the step for the first portion, relativeto the second portion, by storing the video data such that at least oneof a tile spatial resolution, tile temporal resolution, tile colordepth, and tile bit rate is enhanced for the first set of tiles,relative to the second set of tiles.
 33. The system of claim 26,wherein: the subset comprises the first portion and the second portionof the video data; and the processor and/or the data store are furtherconfigured to expedite and/or enhance performance of the step for thefirst portion, relative to the second portion, by performing at leastone of: retrieving the subset of the video data such that the firstportion is retrieved prior to retrieval of the second portion; using thesubset to generate the viewpoint video such that a first segment of theviewpoint video incorporating the first portion of the video data isgenerated prior to generation of a second segment of the viewpoint videoincorporating the second portion of the video data; and using the subsetto generate the viewpoint video such that a first segment of theviewpoint video incorporating the first portion of the video data has ahigher level of quality than a second segment of the viewpoint videoincorporating the second portion of the video data.
 34. The system ofclaim 26, wherein: the data store is further configured to receiveviewing data indicating that one or more viewers prefer or morefrequently view the first portion of the video data over the secondportion of the video data; and the processor is further configured,based on the viewing data, to: assign the first importance metric to thefirst portion of the video data; and assign the second importance metricto the second portion of the video data.
 35. The system of claim 26,further comprising an input device configured to receive user inputindicating that viewing of the first portion is more likely and/orpreferential to viewing of the second portion; wherein the processor isfurther configured to, based on the user input: assign the firstimportance metric to the first portion of the video data; and assign thesecond importance metric to the second portion of the video data. 36.The system of claim 26, wherein the processor is further configured to:carry out analysis of one or both of the video data and audio data thataccompanies the video data to determine that viewing of the firstportion is more likely and/or preferential to viewing of the secondportion; based on the analysis, assign the first importance metric tothe first portion of the video data; and based on the analysis, assignthe second importance metric to the second portion of the video data.